This PDF file contains the editorial “2010 in Review” for OE Vol. 50 Issue 02

This study presents a plastic optical fiber (POF) sensor for measuring the driver's gripping force applied to a steering wheel. This sensor consists of a POF wound around the steering wheel covered with a soft material. The sensing method is based on the bending radiation loss of the POF induced by the driver's gripping force applied to the steering wheel. The bending radiation loss is proportional to the gripping force, and the response time of the POF sensor is about 2 s. The experimental results show that a POF sensor can be effective for monitoring the driver gripping force, and hence driver fatigue.

Image denoising while preserving image features is a key problem in image processing and computer vision. This letter proposes an adaptive mixed method for image restoration. First, this method decomposes a given image as the sum of two components: geometric structure and oscillating pattern according to Meyer's theory. Second, a coupled bidirectional diffusion equation is used to restore the structure part, and a nonlocal means filter is used to remove noise in the oscillating part. Experimental results show advantages of this method in feature-preserving denoising.

A light-driven motor operated by a single source of light is demonstrated for the first time. The device utilizes a NiTi shape memory alloy (SMA) wire initially trained straight shape. The SMA wire was formed in a loop and put around two wheels. In the experiment a steady and continuous rotation was achieved with a bundled loop of 0.3-mm diameter wire. The rotational speed was proportional to the incident light power and 60 rpm was obtained at 3.6 W of light power. The experimental result was consistent with the theory.

We propose a novel method for designing reflectors with large-size spherical surface sources. The center portion of the reflector is designed using the edge-ray principle, while the rim portion is designed based on the variable-separation mapping method. Step discontinuities are introduced during rim surface construction to control the deviation caused by error in normal vectors, and a feedback modification is adopted to compensate for the illuminance deviation produced by the large size of sources. As an example, a streetlamp with a desired rectangular illuminance distribution on the road is designed using a spherical surface source (10 cm diam) and a compact reflector. It has an illuminance uniformity of 60.2% and utilance of 66.9%, considerably improved from the traditional values of 35 and 40%, respectively.

Voice coil actuators (VCAs) are applied in a fast steering mirror (FSM), precision positioning platform, etc. These applications demand that the VCAs used are simple, inexpensive, reliable, and efficient. In this paper, we report a novel VCA with concentration flux-line structure. The VCA greatly reduces the magnet leakage and has less electromagnetic interference with other electronic devices. The output force sensitivity of the VCA is 4.17 N/A with a coil of 300 turns and the stroke is ±2.5 mm. Driven by this VCA, the mechanical scanning angle of the FSM can achieve ±4.9 deg when the scanning frequency is 100 Hz.

We report on the optimization of precision optical component assemblies for space application with respect to mechanical resilience and retention of optical tolerances such as flatness and angles. Optimized parameters include: the cleaning method of the surfaces to be joined; type, concentration, and quantity of the chemical bonding agent; and post-bonding and curing conditions. Experimental studies and quality assurance are complicated by the large statistical spread in breaking stress, which requires the preparation of a large number of samples. The results previously reported in literature have focused primarily on fused silica, rather than space-qualifiable materials such as Zerodur® and ULE®, and have typically addressed only one or two of the parameters. This study provides a comprehensive picture and a better general understanding of what makes a bond reliably strong.

The results of flexural strength testing performed on brittle materials are usually interpreted in light of a "Weibull plot," i.e., by fitting the estimated cumulative failure probability (CFP) to a linearized semiempirical Weibull distribution. This procedure ignores the impact of the testing method on the measured stresses at fracture-specifically, the stressed area and the stress profile-thus resulting in inadequate characterization of the material under investigation. In a previous publication, the author reformulated Weibull's statistical theory of fracture in a manner that emphasizes how the stressed area and the stress profile control the failure probability distribution, which led to the concept of a characteristic strength, that is, the effective strength of a 1-cm₂ uniformly stressed area. Fitting the CFP of IR-transmitting materials (AlON, fusion-cast CaF₂, oxyfluoride glass, fused SiO₂, CVD-ZnSe, and CVD-ZnS) was performed by means of nonlinear regressions but produced evidence of slight, systematic deviations. The purpose of this contribution is to demonstrate that upon extending the previously elaborated model to distributions involving two distinct types of defects-bimodal distributions-the fit agrees with estimated CFPs. Furthermore, the availability of two sets of statistical parameters (characteristic strength and shape parameter) can be taken advantage of to evaluate the failure-probability density, thus providing means of assessing the nature, the critical size, and the size distribution of surface/subsurface flaws.

This paper presents a novel approach of camera calibration under the near-parallel condition based on geometric moments. The near-parallel condition means that the calibration board is near parallel (or parallel) to the imaging plane. A camera calibration model for the near-parallel condition and a calibration board with arranged rectangular features are suggested. Before calibration, feature regions on the image of calibration board are extracted, and centroid and rotation of each feature are detected using geometric moments. These centroids are used for feature points, and meanwhile mean value of rotations is used for the rotation around axis Z. Then, the closed-form solutions to the translations, other two angles and effective focal length are provided by combining Gauss lens model with camera model. Subsequently, principal point is received by radial alignment constraint (RAC), and distortion coefficients are calculated. Finally, all camera parameters are refined by a nonlinear minimization procedure according to the distortion coefficients. Simulations and experiments are performed to verify the proposed camera calibration algorithm. The precision of detecting feature points and calibrating camera parameters are analyzed. The precision of camera calibration results is also evaluated.

We report on an accuracy limit test result of the optical frequency comb technique by comparing the frequencies of two optical frequency combs that operate in two different modes. These two modes are distinguished by the reference frequency for the comb frequency stabilization; an optical frequency (in an optical clock mode) or a microwave frequency (in an optical frequency synthesizer mode). The comparison of the two combs was carried out by simultaneously measuring an absolute frequency of an acetylene-stabilized diode laser with both combs. The frequencies of the two combs agreed with each other within the uncertainty of 16 Hz at 194 THz. The uncertainty is reduced by more than an order compared with a previous report.

We present a high-resolution, high-speed three-dimensional (3-D) shape measurement technique that can reach the speed limit of a digital fringe projection system without significantly increasing the system cost. Instead of generating sinusoidal fringe patterns by a computer directly, they are produced by defocusing binary ones. By this means, with a relatively inexpensive camera, the 3-D shape measurement system can double the previously maximum achievable speed and reach the refreshing rate of a digital-light-processing projector: 120 Hz.

We have developed a calibration approach for a star tracker camera. A modified version of the least-squares iteration algorithm combining Kalman filter is put forward, which allows for autonomous on-orbit calibration of the star tracker camera even with nonlinear camera distortions. In the calibration approach, the optimal principal point and focal length are achieved at first via the modified algorithm, and then the high-order focal-plane distortions are estimated using the solution of the first step. To validate this proposed calibration approach, the real star catalog and synthetic attitude data are adopted to test its performance. The test results have demonstrated the proposed approach performs well in terms of accuracy, robustness, and performance. It can satisfy the autonomous on-orbit calibration of the star tracker camera.

This paper proposes an edge quality assessment system for a submillimeter thick wafer bar suitable for semiconductor and hard disk drive industries. Our key approach is based on Fourier optics analysis in a retro-reflective optical architecture featuring nondestructive and noncontact measurement. In our proposed design, a collimated optical beam is incident on a submillimeter thick wafer bar from its side. In this way, part of the optical beam is reflected back and is then Fourier transformed on a two-dimensional image sensor. By investigating the far-field diffraction pattern, important parameters of the wafer bar such as thickness, surface parallelism, edge parallelism, and surface defect can simultaneously be analyzed. To our knowledge, this is the first time that these important parameters are analyzed by only one system. Other key features include low cost and vibration insensitivity. Our field test study using a 635-nm wavelength laser and a 15-cm plano-convex lens for specified 246-μm thick rectangular wafer bars shows that our retro-reflective approach can measure the bar thickness within its specified ±10 μm. It can also simultaneously evaluate the remaining desired parameters and can distinguish nicely edged bars from poorly edged bars. Other key features include low cost, ease of implementation, robustness, and low component counts.

Because of their spiral wave front, phase singularity, zero-intensity center and orbital angular momentum, dark hollow vortex beams have been found many applications in the field of atom optics such as atom cooling, atom transport and atom guiding. In this paper, a method for generating confluent hypergeometric beam by computer-generated hologram displayed on the spatial light modulator is presented. The hologram is formed by interference between a single ring Laguerre-Gaussian beam and a plane wave. The far-field Fraunhofer diffraction of this optical field transmitted from the hologram is the confluent hypergeometric beam. This beam is a circular symmetric beam which has a phase singularity, spiral wave front, zero-intensity center, and intrinsic orbital angular momentum. It is a new dark hollow vortex beam

A novel method for synthesizing arbitrary-shape triangular-spectrum fiber Bragg gratings (TS-FBGs) is proposed. It involves the use of a discrete layer peeling method for exploiting initial guess and a simulated annealing method for optimizing the desired grating parameter. By comparing it to the reported TS-FBGs synthesis methods, the proposed method has advantages of reducing the maximum index modulation and smoothing index modulation profile simultaneously. We employ the proposed method to synthesize FBGs with symmetric, asymmetric, and right-angled triangular spectrum, all of which have the low and smooth index modulation profiles. The synthesized gratings can act simple and cost-effective wavelength-interrogation devices in optical sensor systems.

In this paper, we analyzed and investigated the nonlinear switching characteristics of an optical device using a double-coupler silicon ring resonator in the presence of the linear losses, the Kerr nonlinearity, two-photon absorption, thermo-optic effects, free-carrier-induced absorption, and dispersion. Results obtained have shown that the general features of the nonlinear switching of the throughput and drop port signals are similar to a single-couple ring and nonlinear Fabry-Perot resonators, respectively. The interesting results of the double-coupler silicon ring resonator are the low switching power conditions and the linear amplification gain. The various applications can be provided by controlling the input-output of silicon-based resonators, for instance, by controlling the coupling ratio, free-carrier lifetime, and input wavelength, in which the multiple applications for optical switches, logic gates, and memories can be provided.

A novel highly birefringent photonic crystal fiber with selectively liquid-filled structure in cladding is proposed. The birefringence is numerically investigated with variant structural parameters and refractive index of the infiltrating liquid. The results show that high birefringence can be achieved over a wide wavelength range, and the birefringence is increased because of the symmetry destroyed further in the proposed structure. However, the confinement loss keeps the same order of magnitude even though more materials with high refractive index are filled in the cladding. By varying the refractive index of the infiltrating liquid, the birefringence is shown to be well tuned. It has the potential to be used as optical devices such as all-fiber polarization controllers and high-sensitive sensors.

Controlling the spatial coherence of the transmitted beam has been suggested as a means of improving the statistics of the received power in long-range free-space optical communications systems. We present an experiment demonstrating the concept of transmitting a partially spatial coherent beam through a turbulent path in a lab setting to overcome long-term dropouts in the received power. It is demonstrated both theoretically and experimentally that using a partially spatial coherent beam can decrease the scintillation index by ∼ 50% and the mean intensity in the simulation by ∼ 90% regardless of turbulence strength, when compared to the intensity of a fully coherent source in turbulence.

We proposed and demonstrated a novel, simple, and low cost method for all-optical clock recovery based on the switching between two injection-locked longitudinal modes in a dc-biased multi-quantum-well Fabry-Perot laser diode (FP-LD). The dc biased FP-LD is simultaneously injection-locked by a return-to-zero data signal at one of the longitudinal modes of the FP-LD and self-seeded at another longitudinal mode by using a uniform fiber Bragg grating as a feedback component. The powers and detunes of the data signal and self-seeding signal are chosen such that self-seeding is realized in the FP-LD only when data signal power is low. Clock signals of data streams at different data rates can be obtained by tuning the optical delay line in the external self-seeding loop. We have demonstrated all-optical clock recovery at 10 GHz. The pulse width, time-bandwidth product, side mode suppression ration, root mean square timing jitter, and average power of the recovered clock signals are 50 ps, 0.5, 50 dB, 248 fs, and 3.6 dBm, respectively. Clock recovery is possible at wavelength within the gain band of the FP-LD. We also find and explore in the experiment the influence of detune between the external data signal and the nearest FP-LD longitudinal mode to the recovered clock.

We propose a novel scheme of communication security using dark-bright soliton conversion behaviors in which the transmission signals can be secured by using the random codes generated by dark-bright soliton conversion within the system. The system consists of two parts, where first, an optical Mach Zhender interferometer (MZI) is used to generate the coincidence dark and bright soliton pair by using the (π/2) phase retarder (i.e., a coupler), in which |D〉 and |B〉 states represent the orthogonal dark and bright soliton pulses. The signals from through (Th) port are formed and transmitted via the transmission line to the end user. Second, the add/drop filter is used to separate(filter) the required signal form the transmission link, in which the Th and drop port signals are formed as a reference and signal, respectively. In this case, we assume that both solitons are input into the MZI ports simultaneously (coincidently), in which the binary codes are randomly formed and used to present the transmission data, in which the states "0" and "1" are represented by |DB〉 and |BD〉, respectively. Finally, the eavesdropper and signal accuracy are also described.

In this paper, we present the design of a very precise collimated fiber array that meets requirements for beam combining. Calculations permit to determine the tolerances toward key parameters and specify the components to manufacture. Thus, the collimated fiber array is composed of a high quality commercial microlens array and an especially dedicated fiber holder that we design and realize experimentally. Manufacture techniques for both the microlens and the holder are chosen to be collective and then compatible with a high number of fibers. With the collimated fiber array hence obtained, the individual beam quality was measured to be λ/10 and the pointing accuracy is under 0.6 mrad.

In radio-requency identification (RFID) systems, when multiple tags transmit data to a reader simultaneously, these data may collide and create unsuccessful identifications; hence, anticollision algorithms are needed to reduce collisions (collision cycles) to improve the tag identification speed. We propose a one-time collision arbitration algorithm to reduce both the number of collisions and the time consumption for tags' identification in RFID. The proposed algorithm uses Manchester coding to detect the locations of collided bits, uses the divide-and-conquer strategy to find the structure of colliding bits to generate 96-bit query strings as the 96-bit candidate query strings (96BCQSs), and uses query-tree anticollision schemes with 96BCQSs to identify tags. The performance analysis and experimental results show that the proposed algorithm has three advantages: (i) reducing the number of collisions to only one, so that the time complexity of tag identification is the simplest O(1), (ii) storing identified identification numbers (IDs) and the 96BCQSs in a register to save the used memory, and (iii) resulting in the number of bits transmitted by both the reader and tags being evidently less than the other algorithms in one-tag identification or in all tags identification.

Holography has a considerable advantage of retrieving three-dimensional information of an object from only one interference recording. However, twin images always appear in the reconstruction for the reason of symmetry. Especially, twin images significantly deteriorate the quality of the reconstructed information in on-axis configuration. A solution of the twin-image problem in a digital holographic microscope by using symmetry with quadrantal masks is suggested in this study. This method is effective to most of the measured area without any additional implements, and restrictions on sample or iterations, and is demonstrated by the simulation and experimental results. The ratio of the disturbed area by a twin-image to the total measured area is reduced to the value of 0.82% in a specific case.

Non-negative matrix factorization (NMF) and its variants have recently been successfully used as dimensionality reduction techniques for identification of the materials present in hyperspectral images. We study a recently introduced variant of NMF called non-negative matrix underapproximation (NMU): it is based on the introduction of underapproximation constraints, which enables one to extract features in a recursive way, such as principal component analysis, but preserving non-negativity. We explain why these additional constraints make NMU particularly well suited to achieve a parts-based and sparse representation of the data, enabling it to recover the constitutive elements in hyperspectral images. Both ℓ2-norm and ℓ1-norm-based minimization of the energy functional are considered. We experimentally show the efficiency of this new strategy on hyperspectral images associated with space object material identification, and on HYDICE and related remote sensing images.

Including multiple sources of information in personal identity recognition and verification gives the opportunity to greatly improve performance. We propose a contactless biometric system that combines two modalities: palmprint and face. Hardware implementations are proposed on the Texas Instrument Digital Signal Processor and Xilinx Field-Programmable Gate Array (FPGA) platforms. The algorithmic chain consists of a preprocessing (which includes palm extraction from hand images), Gabor feature extraction, comparison by Hamming distance, and score fusion. Fusion possibilities are discussed and tested first using a bimodal database of 130 subjects that we designed (uB database), and then two common public biometric databases (AR for face and PolyU for palmprint). High performance has been obtained for recognition and verification purpose: a recognition rate of 97.49% with AR-PolyU database and an equal error rate of 1.10% on the uB database using only two training samples per subject have been obtained. Hardware results demonstrate that preprocessing can easily be performed during the acquisition phase, and multimodal biometric recognition can be treated almost instantly (0.4 ms on FPGA). We show the feasibility of a robust and efficient multimodal hardware biometric system that offers several advantages, such as user-friendliness and flexibility.

We propose an effective method of extracting targets from a region-of-interest (ROI) in infrared images by using a 2-D histogram, considering intensity values and distance values from a center of the ROI. Existing approaches for extracting targets have utilized only intensity values of pixels or an analysis of a 1-D histogram of intensity values. Because the 1-D histogram has mixed bins containing false-negative bins from the target region as well as false-positive bins from the background region, it is difficult to extract target regions effectively due to the mixed bins. In order to solve the problem of the mixed bins, we propose a novel 2-D histogram-based approach for extracting targets. Experimental results have shown that the proposed method achieves better performance of extracting targets than existing methods under various environments, such as target regions with irregular intensities, dim targets, and cluttered backgrounds.

This paper presents stereo vision-based vehicle detection approach on the road using a road feature and disparity histogram. It is not easy to detect only vehicles robustly on the road in various traffic situations, for example, a nonflat road or a multiple-obstacle situation. This paper focuses on the improvement of vehicle detection performance in various real traffic situations. The approach consists of three steps, namely obstacle localization, obstacle segmentation, and vehicle verification. First, we extract a road feature from v-disparity maps binarized using the most frequent values in each row and column, and adopt the extracted road feature as an obstacle criterion in column detection. However, many obstacles still coexist in each localized obstacle area. Thus, we divide the localized obstacle area into multiple obstacles using a disparity histogram and remerge the divided obstacles using four criteria parameters, namely the obstacle size, distance, and angle between the divided obstacles, and the difference of disparity values. Finally, we verify the vehicles using a depth map and gray image to improve the performance. We verify the performance of our proposed method by conducting experiments in various real traffic situations. The average recall rate of vehicle detection is 95.5%.

When compared to the traditional row-column wavelet transform, the line-based wavelet transform can achieve significant memory savings. However, the design of an image codec using the line-based wavelet transform is an intricate task because of the irregular order in which the wavelet coefficients are generated. The independent block coding feature of JPEG2000 makes it work effectively with the line-based wavelet transform. However, with wavelet tree-based image codecs, such as set partitioning in hierarchical trees, the memory usage of the codecs does not realize significant advantage with the line-based wavelet transform because many wavelet coefficients must be buffered before the coding starts. In this paper, the line-based wavelet transform was utilized to facilitate backward coding of wavelet trees (BCWT). Although the BCWT algorithm is a wavelet tree-based algorithm, its coding order differs from that of the traditional wavelet tree-based algorithms, which allows the proposed line-based image codec to become more memory efficient than other line-based image codecs, including line-based JPEG2000, while still offering comparable rate distortion performance and much lower system complexity.

In point-based monomodal image registration, registration accuracy relies heavily on control point (CP) locations and correspondences. However, CP extraction and correspondence establishment are still difficult under complex deformations, such as elastic deformations. To solve this problem, we present a novel approach to optimizing CP locations and simultaneously establishing the proper correspondence between these points. An expectation-maximization-like model and a refinement mechanism are proposed to achieve CP optimization as well as correspondence establishment. Experimental results for artificial and real registration tasks show that the proposed approach is robust and has good convergence behavior.

Most of the traditional evaluation criteria of object classification are based on the error rate, assuming that the costs of different errors are equal. However, the subjective evaluation of the human vision system on such misclassification errors may be unequal. How do we design proper performance evaluation critera taking into account such inequalities is a kernel issue for mimicking the human vision on object classification. We propose the human confusion costs, which are derived from the statistical human confusions on the training and test data sets, for the model learning and the performance evaluation of the generic cost-sensitive object classification problem, respectively. Unlike the manually designed costs, the proposed ones can better represent the properties of human vision. Experimental results on a new data set with annotations from 20 subjects demonstrate the superiority of the proposed costs against other applicable costs.

We propose an algorithm for abnormal event detection in surveillance video. The proposed algorithm is based on a semi-unsupervised learning method, a kind of feature-based approach so that it does not detect the moving object individually. The proposed algorithm identifies dominant flow without individual object tracking using a latent Dirichlet allocation model in crowded environments. It can also automatically detect and localize an abnormally moving object in real-life video. The performance tests are taken with several real-life databases, and their results show that the proposed algorithm can efficiently detect abnormally moving objects in real time. The proposed algorithm can be applied to any situation in which abnormal directions or abnormal speeds are detected regardless of direction.

We present a hybrid generative-discriminative learning method for human action recognition from video sequences. Our model combines a bag-of-words component with supervised latent topic models. A video sequence is represented as a collection of spatiotemporal words by extracting space-time interest points and describing these points using both shape and motion cues. The supervised latent Dirichlet allocation (sLDA) topic model, which employs discriminative learning using labeled data under a generative framework, is introduced to discover the latent topic structure that is most relevant to action categorization. The proposed algorithm retains most of the desirable properties of generative learning while increasing the classification performance though a discriminative setting. It has also been extended to exploit both labeled data and unlabeled data to learn human actions under a unified framework. We test our algorithm on three challenging data sets: the KTH human motion data set, the Weizmann human action data set, and a ballet data set. Our results are either comparable to or significantly better than previously published results on these data sets and reflect the promise of hybrid generative-discriminative learning approaches.

We propose a needle-shape quality-control method. To this end, we have devised a new acquisition system that combines a camera and a backlight. Needle measurements are carried out at a micrometric scale using shadowgraphic image processing. Our method not only distinguishes good needles from bad ones, but also allows classifying flawed needles into various categories of defects. This classification is important because some categories of defects can affect the entire production, whereas others do not. The results of our needle-shape quality-control method are validated using real samples directly off the manufacturing line. Needles are correctly classified at >97%, and accurate measurements on global shape characteristics such as straightness and sharpness are obtained.

This article focuses on the inspection of plastics web materials exhibiting irregular textures such as imitation wood or leather. They are produced in a continuous process at high speed. In this process, various defects occur sporadically. However, current inspection systems for plastics surfaces are able to inspect unstructured products or products with regular, i.e., highly periodic, textures, only. The proposed inspection algorithm uses the local binary pattern operator for texture feature extraction. For classification, semisupervised as well as supervised approaches are used. A simple concept for semisupervised classification is presented and applied for defect detection. The resulting defect-maps are presented to the operator. He assigns class labels that are used to train the supervised classifier in order to distinguish between different defect types. A concept for parallelization is presented allowing the efficient use of standard multicore processor PC hardware. Experiments with images of a typical product acquired in an industrial setting show a detection rate of 97% while achieving a false alarm rate below 1%. Real-time tests show that defects can be reliably detected even at haul-off speeds of 30 m/min. Further applications of the presented concept can be found in the inspection of other materials.

From the perspective of optical cryptanalysis, we propose a method of chosen-plaintext attack against the optical encryption scheme based on joint transform correlator (JTC) architecture. By implementing this attack, an opponent can access the encryption key with the help of the pre-knowledge of a special chosen plaintext and the corresponding ciphertext. It indicates that the optical encryption scheme based on the JTC architecture is vulnerable to chosen-plaintext attack, even though introducing a nonlinear operation into the encryption transform. The validity of this attack is verified by numerical simulations.

This PDF file contains the errata for “OE Vol. 50 Issue 02 Paper OE ERR-FEB2011-1” for OE Vol. 50 Issue 02

This PDF file contains the errata for “OE Vol. 50 Issue 02 Paper OE ERR-FEB2011-2” for OE Vol. 50 Issue 02